https://github.com/pcinereus/SUYR
https://pcinereus.github.io/SUYRs/
26 April, 2022
Course
Topics
| Day | Topic |
|---|---|
| 1 | Intro to Version control (git), reproducible research (rmarkdown) and data wrangling |
| 2 | Data visualisation and Frequentist (generalized) linear models (GLM) |
| 3 | GLM continued + dealing with heterogeneity and autocorrelation |
| 4 | Day 3 continued + Frequentist mixed effects models |
| 5 | Frequentist generalized linear mixed effects models (GLMM) |
| 6 | More GLMM + Frequentist generalized additive models (GAM + GAMM) |
| 7 | GAMM + regression trees |
| 8 | Bayesian linear models |
| 9 | Bayesian generalized linear/generalized mixed effects |
| 10 | Multivariate analyses |
Prep
- Show-us-your-Rs
- R editors
- Rstudio
- Version control / Collaboration
- git/github
- Scripts and reproducible research
- knitr
- lintr/styler
- Rmarkdown / R notebook
R
https://github.com/rstudio/cheatsheets/raw/master/base-r.pdf
R studio
https://github.com/rstudio/cheatsheets/raw/master/rstudio-ide.pdf
Reproducible research
- install
knitrandrmarkdownpackages - R markdown
https://github.com/rstudio/cheatsheets/raw/master/rmarkdown-2.0.pdf
